R version 4.0.3 (2020-10-10) – “Bunny-Wunnies Freak Out”
Packages used for NMDS: vegan (version 2.5-7)
The document shows a series of NMDS ordinations for reference Coastal benthic communities in Virginia with environmental characteristics overlaid to evaluate natural differences in community compositions across coastal regions in Virginia. These NMDS will support the Genus level IBI development process. No West Virginia DEP data is used in this analysis.Reference sites were evaluated by regional biologists.
The dataset used includes all coastal reference stations collected in Virginia that were deemed reference through a series or water quality parameter filters and regional biologist review. Coastal stations were considered to be located in the Southeastern Plains and MidAtlantic Coastal Plains ecoregion. Communities were deemed to have different biological communities based on ordinations conducted on the entire reference dataset as is demonstrated in the document titled “NMDS for Reference Streams”. If stations appeared in the dataset more than 4 times, then the most recent 4 samples were used and the rest removed. Samples that had a total number of taxa below 100 collected at the time of sampling were also removed. Taxa that occurred in the dataset <= 5% of the time were removed. The data was log10 +1 transformed. Environmental factors were compiled for each station and used to plot over the NMDS to show environmental variation associated with the community matrix. The envfit function in Vegan was used to plot the continuous environmental variables. Some environmental variables like precipitation, slope, and elevation have not been calculated for all watersheds yet and will be added at a later date.
The first step was to read in the reference site bug taxa list and environmental factors dataset for each station. Join the environmental dataset with the bug dataset to account for multiple observations of each station and collection date and time.
Check to make sure the bug and environmental join was successful:
Number of rows in Community Matrix: 841
Number or rows in Environmental Matrix: 159
The data was log10+1 transformed. Rare taxa (<=5%) were removed.
## Run 0 stress 0.1941347
## Run 1 stress 0.1941348
## ... Procrustes: rmse 0.0001805422 max resid 0.0008435791
## ... Similar to previous best
## Run 2 stress 0.1943235
## ... Procrustes: rmse 0.007802139 max resid 0.05991985
## Run 3 stress 0.196513
## Run 4 stress 0.194143
## ... Procrustes: rmse 0.00167025 max resid 0.009386494
## ... Similar to previous best
## Run 5 stress 0.1942168
## ... Procrustes: rmse 0.005042973 max resid 0.05594153
## Run 6 stress 0.1941761
## ... Procrustes: rmse 0.004742003 max resid 0.0420407
## Run 7 stress 0.1942097
## ... Procrustes: rmse 0.004186597 max resid 0.02356175
## Run 8 stress 0.1968174
## Run 9 stress 0.1957773
## Run 10 stress 0.1952332
## Run 11 stress 0.1942712
## ... Procrustes: rmse 0.006070419 max resid 0.06212129
## Run 12 stress 0.1941343
## ... New best solution
## ... Procrustes: rmse 0.0003115153 max resid 0.002510636
## ... Similar to previous best
## Run 13 stress 0.1941253
## ... New best solution
## ... Procrustes: rmse 0.003281482 max resid 0.02389589
## Run 14 stress 0.1941516
## ... Procrustes: rmse 0.00331354 max resid 0.02346081
## Run 15 stress 0.1942172
## ... Procrustes: rmse 0.005810283 max resid 0.06101163
## Run 16 stress 0.1955899
## Run 17 stress 0.1941337
## ... Procrustes: rmse 0.003189977 max resid 0.02351722
## Run 18 stress 0.1942802
## ... Procrustes: rmse 0.00717332 max resid 0.04685675
## Run 19 stress 0.1956143
## Run 20 stress 0.1968818
## Run 21 stress 0.1942648
## ... Procrustes: rmse 0.006695186 max resid 0.05262673
## Run 22 stress 0.1941616
## ... Procrustes: rmse 0.003519718 max resid 0.03016268
## Run 23 stress 0.1942231
## ... Procrustes: rmse 0.006794636 max resid 0.06866149
## Run 24 stress 0.1942299
## ... Procrustes: rmse 0.005854429 max resid 0.05689145
## Run 25 stress 0.1941921
## ... Procrustes: rmse 0.004623454 max resid 0.05231941
## Run 26 stress 0.1942835
## ... Procrustes: rmse 0.007246503 max resid 0.06084936
## Run 27 stress 0.1941455
## ... Procrustes: rmse 0.001886242 max resid 0.01663275
## Run 28 stress 0.1956879
## Run 29 stress 0.1941332
## ... Procrustes: rmse 0.003135437 max resid 0.02343558
## Run 30 stress 0.1941292
## ... Procrustes: rmse 0.002720159 max resid 0.02321023
## Run 31 stress 0.1942239
## ... Procrustes: rmse 0.006918485 max resid 0.06919099
## Run 32 stress 0.1941647
## ... Procrustes: rmse 0.003540882 max resid 0.02107171
## Run 33 stress 0.194151
## ... Procrustes: rmse 0.003396378 max resid 0.0227748
## Run 34 stress 0.1942176
## ... Procrustes: rmse 0.005842374 max resid 0.06194309
## Run 35 stress 0.1941261
## ... Procrustes: rmse 0.0002412387 max resid 0.001386587
## ... Similar to previous best
## *** Solution reached
##
## Call:
## metaMDS(comm = coastalFive[, 6:105], k = 3, trymax = 1000)
##
## global Multidimensional Scaling using monoMDS
##
## Data: coastalFive[, 6:105]
## Distance: bray
##
## Dimensions: 3
## Stress: 0.1941253
## Stress type 1, weak ties
## Two convergent solutions found after 35 tries
## Scaling: centring, PC rotation, halfchange scaling
## Species: expanded scores based on 'coastalFive[, 6:105]'
## NMDS1 NMDS2 r2 Pr(>r)
## Year -0.68364 -0.72982 0.0088 0.88
## JulianDate 0.21528 -0.97655 0.3686 0.02 *
## Latitude -0.81004 0.58637 0.3748 0.01 **
## Longitude 0.30112 0.95359 0.0865 0.40
## totalArea_sqMile -0.68700 -0.72666 0.2311 0.02 *
## ELEVMEAN -0.62982 -0.77674 0.2738 0.01 **
## SLPMEAN -0.99798 0.06350 0.4355 0.01 **
## wshdRain_mmyr -0.69052 -0.72332 0.2297 0.02 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 99
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$Season, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Fall Spring
## delta 0.7019 0.7218
## n 68 89
##
## Chance corrected within-group agreement A: 0.01779
## Based on observed delta 0.7132 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$US_L3NAME, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Middle Atlantic Coastal Plain Southeastern Plains
## delta 0.7004 0.7091
## n 25 132
##
## Chance corrected within-group agreement A: 0.02537
## Based on observed delta 0.7077 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$Basin_Code, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Appomattox Chowan-Dismal James-Lower Potomac-Lower Rappahannock
## delta 0.5315 0.7482 0.7037 0.6856 0.6336
## n 3 29 32 6 22
## Small Coastal York
## delta 0.6679 0.6903
## n 21 44
##
## Chance corrected within-group agreement A: 0.05029
## Based on observed delta 0.6896 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$ASSESS_REG, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## NRO PRO TRO
## delta 0.7041 0.6944 0.693
## n 37 99 21
##
## Chance corrected within-group agreement A: 0.04076
## Based on observed delta 0.6965 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##Bioregion: Coastal, No Midges
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$Bioregion, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Coast
## delta 0.7261
## n 157
##
## Chance corrected within-group agreement A: 0
## Based on observed delta 0.7261 and expected delta 0.7261
##
## Significance of delta: 1
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$Gradient, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## MACS Riffle
## delta 0.7249 0.5663
## n 149 8
##
## Chance corrected within-group agreement A: 0.01278
## Based on observed delta 0.7168 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$Order, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## 1 2 3 4 5 6
## delta 0.7083 0.6772 0.6845 0.7332 0.6305 0.4052
## n 33 42 33 33 14 2
##
## Chance corrected within-group agreement A: 0.05055
## Based on observed delta 0.6894 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$StreamCate, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Large Medium Small
## delta 0.7175 0.6845 0.7187
## n 49 33 75
##
## Chance corrected within-group agreement A: 0.02059
## Based on observed delta 0.7112 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$WQS_CLASS, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## III VII
## delta 0.7216 0.7284
## n 116 41
##
## Chance corrected within-group agreement A: 0.003757
## Based on observed delta 0.7234 and expected delta 0.7261
##
## Significance of delta: 0.011
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$BioregionSeason, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## LargeCoastFall LargeCoastSpring MediumCoastFall MediumCoastSpring
## delta 0.7393 0.6719 0.6663 0.6607
## n 20 29 14 19
## SmallCoastFall SmallCoastSpring
## delta 0.6833 0.7312
## n 34 41
##
## Chance corrected within-group agreement A: 0.04066
## Based on observed delta 0.6966 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:105], grouping = samplescoresenv_coast$Bioregionsize, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## LargeCoast MediumCoast SmallCoast
## delta 0.7175 0.6845 0.7187
## n 49 33 75
##
## Chance corrected within-group agreement A: 0.02059
## Based on observed delta 0.7112 and expected delta 0.7261
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999